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Computational Pathology and Ophthalmic Medical Image Analysis

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Cover of 'Computational Pathology and Ophthalmic Medical Image Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 Improving Accuracy of Nuclei Segmentation by Reducing Histological Image Variability
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    Chapter 2 Multi-resolution Networks for Semantic Segmentation in Whole Slide Images
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    Chapter 3 Improving High Resolution Histology Image Classification with Deep Spatial Fusion Network
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    Chapter 4 Construction of a Generative Model of H&E Stained Pathology Images of Pancreas Tumors Conditioned by a Voxel Value of MRI Image
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    Chapter 5 Accurate 3D Reconstruction of a Whole Pancreatic Cancer Tumor from Pathology Images with Different Stains
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    Chapter 6 Role of Task Complexity and Training in Crowdsourced Image Annotation
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    Chapter 7 Capturing Global Spatial Context for Accurate Cell Classification in Skin Cancer Histology
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    Chapter 8 Exploiting Multiple Color Representations to Improve Colon Cancer Detection in Whole Slide H&E Stains
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    Chapter 9 Leveraging Unlabeled Whole-Slide-Images for Mitosis Detection
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    Chapter 10 Evaluating Out-of-the-Box Methods for the Classification of Hematopoietic Cells in Images of Stained Bone Marrow
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    Chapter 11 DeepCerv: Deep Neural Network for Segmentation Free Robust Cervical Cell Classification
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    Chapter 12 Whole Slide Image Registration for the Study of Tumor Heterogeneity
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    Chapter 13 Modality Conversion from Pathological Image to Ultrasonic Image Using Convolutional Neural Network
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    Chapter 14 Structure Instance Segmentation in Renal Tissue: A Case Study on Tubular Immune Cell Detection
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    Chapter 15 Cellular Community Detection for Tissue Phenotyping in Histology Images
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    Chapter 16 Automatic Detection of Tumor Budding in Colorectal Carcinoma with Deep Learning
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    Chapter 17 Significance of Hyperparameter Optimization for Metastasis Detection in Breast Histology Images
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    Chapter 18 Image Magnification Regression Using DenseNet for Exploiting Histopathology Open Access Content
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    Chapter 19 Uncertainty Driven Pooling Network for Microvessel Segmentation in Routine Histology Images
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    Chapter 20 Ocular Structures Segmentation from Multi-sequences MRI Using 3D Unet with Fully Connected CRFs
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    Chapter 21 Classification of Findings with Localized Lesions in Fundoscopic Images Using a Regionally Guided CNN
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    Chapter 22 Segmentation of Corneal Nerves Using a U-Net-Based Convolutional Neural Network
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    Chapter 23 Automatic Pigmentation Grading of the Trabecular Meshwork in Gonioscopic Images
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    Chapter 24 Large Receptive Field Fully Convolutional Network for Semantic Segmentation of Retinal Vasculature in Fundus Images
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    Chapter 25 Explaining Convolutional Neural Networks for Area Estimation of Choroidal Neovascularization via Genetic Programming
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    Chapter 26 Joint Segmentation and Uncertainty Visualization of Retinal Layers in Optical Coherence Tomography Images Using Bayesian Deep Learning
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    Chapter 27 cGAN-Based Lacquer Cracks Segmentation in ICGA Image
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    Chapter 28 Localizing Optic Disc and Cup for Glaucoma Screening via Deep Object Detection Networks
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    Chapter 29 Fundus Image Quality-Guided Diabetic Retinopathy Grading
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    Chapter 30 DeepDisc: Optic Disc Segmentation Based on Atrous Convolution and Spatial Pyramid Pooling
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    Chapter 31 Large-Scale Left and Right Eye Classification in Retinal Images
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    Chapter 32 Automatic Segmentation of Cortex and Nucleus in Anterior Segment OCT Images
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    Chapter 33 Local Estimation of the Degree of Optic Disc Swelling from Color Fundus Photography
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    Chapter 34 Visual Field Based Automatic Diagnosis of Glaucoma Using Deep Convolutional Neural Network
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    Chapter 35 Towards Standardization of Retinal Vascular Measurements: On the Effect of Image Centering
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    Chapter 36 Feasibility Study of Subfoveal Choroidal Thickness Changes in Spectral-Domain Optical Coherence Tomography Measurements of Macular Telangiectasia Type 2
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    Chapter 37 Segmentation of Retinal Layers in OCT Images of the Mouse Eye Utilizing Polarization Contrast
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    Chapter 38 Glaucoma Diagnosis from Eye Fundus Images Based on Deep Morphometric Feature Estimation
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    Chapter 39 2D Modeling and Correction of Fan-Beam Scan Geometry in OCT
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    Chapter 40 A Bottom-Up Saliency Estimation Approach for Neonatal Retinal Images
Overall attention for this book and its chapters
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Mentioned by

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11 tweeters

Citations

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Title
Computational Pathology and Ophthalmic Medical Image Analysis
Published by
Springer International Publishing, December 2018
DOI 10.1007/978-3-030-00949-6
ISBNs
978-3-03-000948-9, 978-3-03-000949-6
Editors

Stoyanov, Danail, Taylor, Zeike, Ciompi, Francesco, Xu, Yanwu, Martel, Anne, Maier-Hein, Lena, Rajpoot, Nasir, van der Laak, Jeroen, Veta, Mitko, McKenna, Stephen, Snead, David, Trucco, Emanuele, Garvin, Mona K., Chen, Xin Jan, Bogunovic, Hrvoje

Twitter Demographics

The data shown below were collected from the profiles of 11 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 18%
Student > Master 8 18%
Researcher 5 11%
Student > Bachelor 3 7%
Other 3 7%
Other 8 18%
Unknown 9 20%
Readers by discipline Count As %
Computer Science 18 41%
Engineering 8 18%
Agricultural and Biological Sciences 3 7%
Business, Management and Accounting 2 5%
Energy 1 2%
Other 2 5%
Unknown 10 23%